Knowledge of protein structure is key for studying mechanisms of protein function, and the Protein Data Bank (PDB), the main open repository of protein structures, has been of tremendous value since its inception 50 years a go. While PDB structures are mostly static, the functions of proteins almost always involve motion and conformational changes, and a complete picture of protein function requires an understanding of structural dynamics. The development of a structural proteomics tool called LiP-MS at ETHZ enabled probing the dynamic structural changes of proteins in situ in response to a variety of perturbations and on a proteome-wide scale. The approach found a broad range of applications in biology, biomedicine and drug development. The aim of this project is to set up the first open research data infrastructure for storage and dissemination of these unique dynamic and in situ protein structural data. The infrastructure will make LiP-MS data findable, accessible, and re-usable by the scientific community. Specifically, we aimed at identifying guidelines for the analysis and reporting of LiP-MS-based dynamic structural data, as a joint effort of data producers and data consumers (Aim 1). Next, we aimed at developing a web-based, open-access repository of dynamic structural data (Aim 2) and populating this repository with dynamic structural data for ~25,000 proteins from six organisms. We believe that this resource will be highly relevant for a large number of users from different communities. In this reporting period (total grant duration), we interacted with LiP-MS data producers, data consumers, service providers and statisticians to identify the specific features of LiP-MS data that required standardization. Based on this, we: 1. Addressed the need to correct LiP-MS data for protein abundance changes and modifications before reporting; 2. Developed a standardized score to report the probability of an amino acid residue to be involved in a conformational change, along the sequence of a protein and 3. Assessed the information content and analytical reliability of the different types of peptides generated by the LiP-MS workflow. These developments resulted in guidelines on the standardization of LiP-MS data. Next, we developed a web-accessible database to store LiP-MS data and make them publicly available and resusable. The database (which we ultimately called “DynaProt” due to its focus on protein dynamics) supports usage of LiP-MS data by non-proteomics experts (e.g. biologists, biomedical scientists, Pharma and Biotech) and their exploration in the context of three-dimensional structures of proteins and available functional information. We will soon release the database and submit a manuscript describing its creation and its application to the study of protein dynamics. Two additional manuscripts were published or are under review on the standardization of LiP-MS data.